Evaluating DayCent and STICS in simulating the long-term impact of contrasting organic resource amendments on soil organic carbon and maize yields in sub-Saharan Africa
Year: 2025
Type: article
Abstract: Problem Low crop yields in sub-Saharan Africa mainly result from low soil fertility and insufficient nutrient inputs. A key component of Integrated Soil Fertility Management (ISFM), namely combining inputs of mineral fertilizers and organic resources, presents an opportunity to boost yields and maintain soil organic carbon (SOC) stocks in the long run. Soil-crop models help to assess the performance of ISFM under contrasting soil, climate, and management combinations. Yet, to date, most soil-crop models have been calibrated and tested in temperate conditions. Objective Our objective was to evaluate and compare the performance of two different soil-crop models, DayCent and STICS, to represent crop yields and SOC dynamics under contrasting organic resource amendments. Methods We used a large dataset representing 3384 cropping situations (site x season x treatment) from four long-term experiments in Kenya. Each experiment included the same treatments with the addition of two quantities of low- to high-quality organic resource amendments (high vs low C/N ratio, respectively), with (+N) and without (-N) mineral nitrogen fertilizer. Each treatment included a cropped and uncropped subplot, allowing for a unique stepwise calibration of soil and crop parameters. Results Both models represented SOC and yield dynamics with similar accuracy across sites and treatments. They reproduced SOC dynamics well (nRMSE below 30 %) in the two clayey soils sites but not in the two sandy soils. Yet, in most sites they reproduced well SOC differences between high (Farmyard manure, Thithonia and Calliandra ) and low-quality (maize stover and sawdust) organic resources . Models reproduced the average yield across sites and treatments similarly. They reproduced the positive effects of high-quality organic resources and the addition of mineral N on maize yield well. Models had similar inaccuracy in reproducing yield and yield variability under poor-quality organic resources and -N treatments. Conclusion The stepwise calibration approach used in this study enabled highlighting the models’ strengths and weaknesses in soil and plant simulations. The results suggest that the two models have similar strengths and struggle with the same problems despite having different structures. Collecting detailed plant (leaf area index, plant N uptake) and soil (water, nitrogen dynamics) in-season data from long-term experiments will be critical to exploit the full model complexity and improve their accuracy for tropical conditions.
Source: Field Crops Research
Institutions: Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Agro-écologie et intensification durable des cultures annuelles, ETH Zurich, Université de Montpellier, University of Zimbabwe, Centro Internacional de Mejoramiento de Maíz Y Trigo, International Maize and Wheat Improvement Center, International Maize and Wheat Improvement Center, Kenyatta University, University of Embu, International Institute of Tropical Agriculture, International Institute of Tropical Agriculture, International Institute of Tropical Agriculture
Language: English
Subfield: Soil Science
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,680
Funders: Agropolis Fondation, University of Embu, Kenyatta University, Agence Nationale de la Recherche, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Eidgenössische Technische Hochschule Zürich, Total Foundation, Horizon 2020 Framework Programme, HORIZON EUROPE European Research Council, International Institute of Tropical Agriculture
OpenAlex ID: W4414800909
